Researchers can now make neighborhood voting predictions from Google Street View images


In a sign that computers will be able to perform image analysis as fluently as text analysis, a group of Stanford-based researchers were able to make accurate predictions about neighborhood voting patterns based on millions of pictures collected from Google Street View, reports The New York Times. While other academic projects have used artificial intelligence to mine Google Street View for socioconomic insights (such as Streetchange), this project is notable because of the vast quantity of images that its AI software processed.

Led by Stanford computer vision scientist Timnit Gebru, the team of researchers used software to analyze 50 million images of street scenes and location data. Their goal was to find data that could be used to predict demographic statistics at the zip code…

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